class_docstr: Implementations of DRL algorithms
  Attributes
  ----------
      env: gym environment class
          user-defined class
  Methods
  -------
      get_model()
          setup DRL algorithms
      train_model()
          train DRL algorithms in a train dataset
          and output the trained model
      DRL_prediction()
          make a prediction in a test dataset and get results
code: def __init__(self, env, price_array, tech_array, turbulence_array):
      self.env = env
      self.price_array = price_array
      self.tech_array = tech_array
      self.turbulence_array = turbulence_array
  
file_path: FinRL/finrl/agents/elegantrl/models.py
imports: from __future__ import annotations
  import torch
  from elegantrl.agents import *
  from elegantrl.train.config import Config
  from elegantrl.train.run import train_agent
label_desc: Use image node_id 1 to create a new DRLAgent object  with example: obj = DRLAgent(env, price_array, tech_array, turbulence_array)